Secrecy Offloading Rate Maximization for Multi-Access Mobile Edge Computing Networks

This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, base stations, and malicious eavesdropper. Specifically, the users adopt partial offloading strategy by partitioning computation task into several parts. One is executed locally others are securely offloaded to MEC servers integrated stations leveraging physical layer security combat eavesdropping. We jointly optimize power allocation, partition, subcarrier resource maximize secrecy rate subject communication constraints. Numerical results demonstrate that our proposed schemes outperform benchmark substantially emphasize necessity conducting over servers.